ScreenIT
The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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AVIFAVIR for Treatment of Patients With Moderate Coronavirus Disease 2019 (COVID-19): Interim Results of a Phase II/III Multicenter Randomized Clinical Trial
This article has 21 authors:Reviewed by ScreenIT
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Incidence and Characteristics of Co-infection and Secondary Infection in Patients with COVID-19
This article has 17 authors:Reviewed by ScreenIT
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SLAMF7 engagement super-activates macrophages in acute and chronic inflammation
This article has 13 authors:Reviewed by ScreenIT
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Acceptance of COVID-19 vaccine in Pakistan among health care workers
This article has 3 authors:Reviewed by ScreenIT
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Potential Achilles heels of SARS-CoV-2 are best displayed by the base order-dependent component of RNA folding energy
This article has 2 authors:Reviewed by ScreenIT
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COVID-19 case forecasting model for Sri Lanka based on Stringency Index
This article has 8 authors:Reviewed by ScreenIT
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Optical genome mapping identifies rare structural variations as predisposition factors associated with severe COVID-19
This article has 26 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Comprehensive Genome Analysis of 6,000 USA SARS-CoV-2 Isolates Reveals Haplotype Signatures and Localized Transmission Patterns by State and by Country
This article has 5 authors:Reviewed by ScreenIT
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The Silent Pandemic COVID-19 in the Asymptomatic Population
This article has 2 authors:Reviewed by ScreenIT
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COVI-Prim survey: Challenges for Austrian and German general practitioners during initial phase of COVID-19
This article has 8 authors:Reviewed by ScreenIT